The acquisition and recognition of fingerprints have today become inescapable in the context of the checking of the identity of persons. Current systems for acquiring fingerprints comprise a hardware component and a software component. The hardware component relies essentially on the implementation of a sensor allowing the acquisition of an image of the finger whose print it is sought to acquire. The software component comprises a man-machine interface allowing the acquisition of details, the recording of personal data, the displaying of information intended for the operator and the subject.
Moreover, currently, an aim of fingerprint acquisition software consists increasingly in detecting possible attempted frauds of these systems, through the use of fake fingers, such as molded fingers, latex fingers, etc. These frauds may be motivated by a wish to hide one's identity so as not to be recognized, to usurp somebody's identity, or else to seek to create a fake identity for example. To guarantee the effectiveness of the fingerprint acquisition stations, it is important to develop systems for detecting these attempted frauds.
The invention lies in this context of searching for more effective solutions aimed at detecting fake fingers, by way of a software approach to the problem.
The prior art comprises a certain number of technical solutions making it possible to detect fake fingers. In particular, several technologies based on a hardware approach to the issue have been developed, such as that described in patent U.S. Pat. No. 7,415,139; they usually consist in determining whether the finger for which the image is acquired is indeed alive, by way of measurements of temperatures, blood flow, or by detecting sweating phenomena for example. Other technologies are based on an analysis of the image of the print of the finger; such techniques are for example disclosed in publications such as R. DERAKHSHANI ET AL, “Determination of vitality from a non-invasive biomedical measurement for use in fingerprint scanners”, in Pattern Recognition, v 36, n 2, p 383-96, February 2003, or else in S. NIKAM ET AL, “Wavelet energy signature and GLCM features based fingerprint anti-spoofing”, for Sixth IIEEE International conference on Wavelet Analysis and Pattern Recognition (ICWAPR-2008), Hong Kong, 30-31 Aug. 2008, to give an example proposing a wavelet analysis of the image acquired.